Proton pump inhibitors and the risk of inflammatory bowel disease: population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine whether the use of proton pump inhibitors (PPIs) compared with the use of histamine-2 receptor antagonists (H2RAs) is associated with an increased risk of inflammatory bowel disease (IBD). DESIGN: Population-based cohort study designed to address the impact of protopathic bias. SETTING: General practices contributing data to the UK Clinical Practice Research Datalink GOLD. PARTICIPANTS: 1 498 416 initiators of PPIs and 322 474 initiators of H2RAs from 1 January 1990 to 31 December 2018, with follow-up until 31 December 2019. Patients were analysed according to the timing of the IBD diagnosis after treatment initiation (early vs late). MAIN OUTCOME MEASURES: Standardised morbidity ratio weighted Cox proportional hazards models were used to estimate marginal HRs and 95% CIs. In the early-event analysis, IBD diagnoses were assessed within the first 2 years of treatment initiation, an analysis subject to potential protopathic bias. In the late-event analysis, all exposures were lagged by 2 years to account for latency and minimise protopathic bias. RESULTS: In the early-event analysis, the use of PPIs was associated with an increased risk of IBD within the first 2 years of treatment initiation, compared with H2RAs (HR 1.39, 95% CI 1.14 to 1.69). In contrast, the use of PPIs was not associated with an increased risk of IBD in the late-event analysis (HR 1.05, 95% CI 0.90 to 1.22). The results remained consistent in several sensitivity analyses. CONCLUSIONS: Compared with H2RAs, PPIs were not associated with an increased risk of IBD, after accounting for protopathic bias.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".